基于决策树的车载CAN总线异常检测技术研究

Research on Vehicle CAN Bus Abnormal Detection Technology Based on Decision Tree

针对目前CAN总线异常检测方法无法检测出异常情况等缺点,设计研究了基于决策树的车载CAN总线异常检测技术。构建了决策树CAN总线异常检测模型,详细阐述了决策树模型生成流程以及车载CAN总线报文异常检测流程。另外对CAN总线数据决策树生成算法进行设计说明。最后针对该设计方法进行了实验仿真分析,结果表明其能够相对非常准确的检测定位出异常报文,这为后续的研究奠定了基础。

In view of the current CAN bus anomaly detection method can not detect the abnormal situation and other shortcomings,designed a vehicle CAN bus anomaly detection technology based on decision tree. The decision tree CAN anomaly detection model is constructed,and the decision tree model generation process and the CAN bus message anomaly detection process are described in detail. In addition,the CAN bus data decision tree generation algorithm is described. Finally,an experimental simulation analysis is carried out for the design method. The results show that it can locate the abnormal message with relatively accurate detection,which lays the foundation for the follow-up study.